Technical Papers

Planning & Terrain

Tuesday, 27 July | 2:00 PM - 3:30 PM | Room 502 B

Session Chair:
Michiel van de Panne, The University of British Columbia

Robust Physics-Based Locomotion Using Low-Dimensional Planning

A physics-based locomotion controller based on online planning. Using an optimization that plans over multiple locomotion phases, different gaits and transitions, including walking, running, and jumping, emerge naturally. These controllers can traverse challenging terrain and withstand large disturbances.

Igor Mordatch
University of Toronto

Martin de Lasa
University of Toronto

Aaron Hertzmann
University of Toronto

Terrain-Adaptive Bipedal Locomotion Control

A framework for generation of agile biped locomotion controllers that adapt to uneven terrain. The paper demonstrates these controllers in navigation tasks performing both gradual and sharp turns, and transitioning between moving forward, backward, and sideways on uneven terrain according to interactive user commands.

Jia-chi Wu
University of Washington

Zoran Popović
University of Washington

Optimizing Walking Controllers for Uncertain Inputs and Environments

This paper introduces methods for optimizing physics-based walking controllers for robustness to uncertainty. Controller synthesis entails maximizing the expected value of the reward, which is computed by Monte Carlo evaluation. Optimizing control strategies with uncertain inputs and environmental factors increases robustness and produces natural variations in style.

Jack M. Wang
University of Toronto

David J. Fleet
University of Toronto

Aaron Hertzmann
University of Toronto

Optimal Feedback Control for Character Animation Using an Abstract Model

A new approach to controlling real-time virtual characters under physical perturbations and changes in the environment. Given a reference motion sequence, the authors seek to design an optimal feedback controller that allows for long-term re-planning and timing adjustment.